[Core] Support dynamically loading Lora adapter from HuggingFace (#6234)

Co-authored-by: Antoni Baum <antoni.baum@protonmail.com>

vllm/lora/utils.py

@@ -1,5 +1,9 @@
+import os
 from typing import List, Optional, Set, Tuple, Type
 
+import huggingface_hub
+from huggingface_hub.utils import (EntryNotFoundError, HfHubHTTPError,
+                                   HFValidationError, RepositoryNotFoundError)
 from torch import nn
 from transformers import PretrainedConfig
 
@@ -105,3 +109,46 @@ def parse_fine_tuned_lora_name(name: str) -> Tuple[str, bool]:
             return ".".join(parts[2:-1]), parts[-1] == "lora_embedding_A"
 
     raise ValueError(f"{name} is unsupported LoRA weight")
+
+
+def get_adapter_absolute_path(lora_path: str) -> str:
+    """
+    Resolves the given lora_path to an absolute local path.
+
+    If the lora_path is identified as a Hugging Face model identifier,
+    it will download the model and return the local snapshot path.
+    Otherwise, it treats the lora_path as a local file path and
+    converts it to an absolute path.
+
+    Parameters:
+    lora_path (str): The path to the lora model, which can be an absolute path,
+                     a relative path, or a Hugging Face model identifier.
+
+    Returns:
+    str: The resolved absolute local path to the lora model.
+    """
+
+    # Check if the path is an absolute path. Return it no matter exists or not.
+    if os.path.isabs(lora_path):
+        return lora_path
+
+    # If the path starts with ~, expand the user home directory.
+    if lora_path.startswith('~'):
+        return os.path.expanduser(lora_path)
+
+    # Check if the expanded relative path exists locally.
+    if os.path.exists(lora_path):
+        return os.path.abspath(lora_path)
+
+    # If the path does not exist locally, assume it's a Hugging Face repo.
+    try:
+        local_snapshot_path = huggingface_hub.snapshot_download(
+            repo_id=lora_path)
+    except (HfHubHTTPError, RepositoryNotFoundError, EntryNotFoundError,
+            HFValidationError):
+        # Handle errors that may occur during the download
+        # Return original path instead instead of throwing error here
+        logger.exception("Error downloading the HuggingFace model")
+        return lora_path
+
+    return local_snapshot_path